X-Git-Url: https://git.sesse.net/?a=blobdiff_plain;f=src%2Fnnue%2Fevaluate_nnue.cpp;h=ef6b7e91a606c14056c1de3cd261039bd3832ab4;hb=ec02714b6262e26d6f96c45c4e2527f3d382a9f8;hp=4a3c206b8087fcb065ad0b9c4e595c68495701a8;hpb=f193778446acc6e60d7f0f99c6eb01489f89e962;p=stockfish diff --git a/src/nnue/evaluate_nnue.cpp b/src/nnue/evaluate_nnue.cpp index 4a3c206b..ef6b7e91 100644 --- a/src/nnue/evaluate_nnue.cpp +++ b/src/nnue/evaluate_nnue.cpp @@ -1,6 +1,6 @@ /* Stockfish, a UCI chess playing engine derived from Glaurung 2.1 - Copyright (C) 2004-2021 The Stockfish developers (see AUTHORS file) + Copyright (C) 2004-2023 The Stockfish developers (see AUTHORS file) Stockfish is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by @@ -18,178 +18,412 @@ // Code for calculating NNUE evaluation function +#include "evaluate_nnue.h" + +#include +#include +#include +#include +#include #include -#include +#include +#include #include "../evaluate.h" -#include "../position.h" #include "../misc.h" -#include "../uci.h" +#include "../position.h" #include "../types.h" - -#include "evaluate_nnue.h" +#include "../uci.h" +#include "nnue_accumulator.h" +#include "nnue_common.h" namespace Stockfish::Eval::NNUE { - // Input feature converter - LargePagePtr featureTransformer; +// Input feature converter +LargePagePtr featureTransformer; - // Evaluation function - AlignedPtr network[LayerStacks]; +// Evaluation function +AlignedPtr network[LayerStacks]; - // Evaluation function file name - std::string fileName; - std::string netDescription; +// Evaluation function file name +std::string fileName; +std::string netDescription; - namespace Detail { +namespace Detail { - // Initialize the evaluation function parameters - template - void initialize(AlignedPtr& pointer) { +// Initialize the evaluation function parameters +template +void initialize(AlignedPtr& pointer) { pointer.reset(reinterpret_cast(std_aligned_alloc(alignof(T), sizeof(T)))); std::memset(pointer.get(), 0, sizeof(T)); - } +} - template - void initialize(LargePagePtr& pointer) { +template +void initialize(LargePagePtr& pointer) { - static_assert(alignof(T) <= 4096, "aligned_large_pages_alloc() may fail for such a big alignment requirement of T"); + static_assert(alignof(T) <= 4096, + "aligned_large_pages_alloc() may fail for such a big alignment requirement of T"); pointer.reset(reinterpret_cast(aligned_large_pages_alloc(sizeof(T)))); std::memset(pointer.get(), 0, sizeof(T)); - } +} - // Read evaluation function parameters - template - bool read_parameters(std::istream& stream, T& reference) { +// Read evaluation function parameters +template +bool read_parameters(std::istream& stream, T& reference) { std::uint32_t header; header = read_little_endian(stream); - if (!stream || header != T::get_hash_value()) return false; + if (!stream || header != T::get_hash_value()) + return false; return reference.read_parameters(stream); - } +} - // Write evaluation function parameters - template - bool write_parameters(std::ostream& stream, const T& reference) { +// Write evaluation function parameters +template +bool write_parameters(std::ostream& stream, const T& reference) { write_little_endian(stream, T::get_hash_value()); return reference.write_parameters(stream); - } +} - } // namespace Detail +} // namespace Detail - // Initialize the evaluation function parameters - void initialize() { + +// Initialize the evaluation function parameters +static void initialize() { Detail::initialize(featureTransformer); for (std::size_t i = 0; i < LayerStacks; ++i) - Detail::initialize(network[i]); - } + Detail::initialize(network[i]); +} - // Read network header - bool read_header(std::istream& stream, std::uint32_t* hashValue, std::string* desc) - { +// Read network header +static bool read_header(std::istream& stream, std::uint32_t* hashValue, std::string* desc) { std::uint32_t version, size; - version = read_little_endian(stream); - *hashValue = read_little_endian(stream); - size = read_little_endian(stream); - if (!stream || version != Version) return false; + version = read_little_endian(stream); + *hashValue = read_little_endian(stream); + size = read_little_endian(stream); + if (!stream || version != Version) + return false; desc->resize(size); stream.read(&(*desc)[0], size); return !stream.fail(); - } +} - // Write network header - bool write_header(std::ostream& stream, std::uint32_t hashValue, const std::string& desc) - { +// Write network header +static bool write_header(std::ostream& stream, std::uint32_t hashValue, const std::string& desc) { write_little_endian(stream, Version); write_little_endian(stream, hashValue); - write_little_endian(stream, desc.size()); + write_little_endian(stream, std::uint32_t(desc.size())); stream.write(&desc[0], desc.size()); return !stream.fail(); - } +} - // Read network parameters - bool read_parameters(std::istream& stream) { +// Read network parameters +static bool read_parameters(std::istream& stream) { std::uint32_t hashValue; - if (!read_header(stream, &hashValue, &netDescription)) return false; - if (hashValue != HashValue) return false; - if (!Detail::read_parameters(stream, *featureTransformer)) return false; + if (!read_header(stream, &hashValue, &netDescription)) + return false; + if (hashValue != HashValue) + return false; + if (!Detail::read_parameters(stream, *featureTransformer)) + return false; for (std::size_t i = 0; i < LayerStacks; ++i) - if (!Detail::read_parameters(stream, *(network[i]))) return false; + if (!Detail::read_parameters(stream, *(network[i]))) + return false; return stream && stream.peek() == std::ios::traits_type::eof(); - } +} - // Write network parameters - bool write_parameters(std::ostream& stream) { +// Write network parameters +static bool write_parameters(std::ostream& stream) { - if (!write_header(stream, HashValue, netDescription)) return false; - if (!Detail::write_parameters(stream, *featureTransformer)) return false; + if (!write_header(stream, HashValue, netDescription)) + return false; + if (!Detail::write_parameters(stream, *featureTransformer)) + return false; for (std::size_t i = 0; i < LayerStacks; ++i) - if (!Detail::write_parameters(stream, *(network[i]))) return false; - return (bool)stream; - } + if (!Detail::write_parameters(stream, *(network[i]))) + return false; + return bool(stream); +} + +void hint_common_parent_position(const Position& pos) { + featureTransformer->hint_common_access(pos); +} - // Evaluation function. Perform differential calculation. - Value evaluate(const Position& pos, bool adjusted) { +// Evaluation function. Perform differential calculation. +Value evaluate(const Position& pos, bool adjusted, int* complexity) { // We manually align the arrays on the stack because with gcc < 9.3 // overaligning stack variables with alignas() doesn't work correctly. constexpr uint64_t alignment = CacheLineSize; + constexpr int delta = 24; #if defined(ALIGNAS_ON_STACK_VARIABLES_BROKEN) - TransformedFeatureType transformedFeaturesUnaligned[ - FeatureTransformer::BufferSize + alignment / sizeof(TransformedFeatureType)]; - char bufferUnaligned[Network::BufferSize + alignment]; + TransformedFeatureType + transformedFeaturesUnaligned[FeatureTransformer::BufferSize + + alignment / sizeof(TransformedFeatureType)]; auto* transformedFeatures = align_ptr_up(&transformedFeaturesUnaligned[0]); - auto* buffer = align_ptr_up(&bufferUnaligned[0]); #else - alignas(alignment) - TransformedFeatureType transformedFeatures[FeatureTransformer::BufferSize]; - alignas(alignment) char buffer[Network::BufferSize]; + alignas(alignment) TransformedFeatureType transformedFeatures[FeatureTransformer::BufferSize]; #endif ASSERT_ALIGNED(transformedFeatures, alignment); - ASSERT_ALIGNED(buffer, alignment); - const std::size_t bucket = (pos.count() - 1) / 4; - const auto psqt = featureTransformer->transform(pos, transformedFeatures, bucket); - const auto output = network[bucket]->propagate(transformedFeatures, buffer); + const int bucket = (pos.count() - 1) / 4; + const auto psqt = featureTransformer->transform(pos, transformedFeatures, bucket); + const auto positional = network[bucket]->propagate(transformedFeatures); + + if (complexity) + *complexity = abs(psqt - positional) / OutputScale; + + // Give more value to positional evaluation when adjusted flag is set + if (adjusted) + return static_cast(((1024 - delta) * psqt + (1024 + delta) * positional) + / (1024 * OutputScale)); + else + return static_cast((psqt + positional) / OutputScale); +} - int materialist = psqt; - int positional = output[0]; +struct NnueEvalTrace { + static_assert(LayerStacks == PSQTBuckets); - int delta_npm = abs(pos.non_pawn_material(WHITE) - pos.non_pawn_material(BLACK)); - int entertainment = (adjusted && delta_npm <= BishopValueMg - KnightValueMg ? 7 : 0); + Value psqt[LayerStacks]; + Value positional[LayerStacks]; + std::size_t correctBucket; +}; + +static NnueEvalTrace trace_evaluate(const Position& pos) { + + // We manually align the arrays on the stack because with gcc < 9.3 + // overaligning stack variables with alignas() doesn't work correctly. + constexpr uint64_t alignment = CacheLineSize; - int A = 128 - entertainment; - int B = 128 + entertainment; +#if defined(ALIGNAS_ON_STACK_VARIABLES_BROKEN) + TransformedFeatureType + transformedFeaturesUnaligned[FeatureTransformer::BufferSize + + alignment / sizeof(TransformedFeatureType)]; - int sum = (A * materialist + B * positional) / 128; + auto* transformedFeatures = align_ptr_up(&transformedFeaturesUnaligned[0]); +#else + alignas(alignment) TransformedFeatureType transformedFeatures[FeatureTransformer::BufferSize]; +#endif - return static_cast( sum / OutputScale ); - } + ASSERT_ALIGNED(transformedFeatures, alignment); - // Load eval, from a file stream or a memory stream - bool load_eval(std::string name, std::istream& stream) { + NnueEvalTrace t{}; + t.correctBucket = (pos.count() - 1) / 4; + for (IndexType bucket = 0; bucket < LayerStacks; ++bucket) + { + const auto materialist = featureTransformer->transform(pos, transformedFeatures, bucket); + const auto positional = network[bucket]->propagate(transformedFeatures); + + t.psqt[bucket] = static_cast(materialist / OutputScale); + t.positional[bucket] = static_cast(positional / OutputScale); + } + + return t; +} + +constexpr std::string_view PieceToChar(" PNBRQK pnbrqk"); + + +// Converts a Value into (centi)pawns and writes it in a buffer. +// The buffer must have capacity for at least 5 chars. +static void format_cp_compact(Value v, char* buffer) { + + buffer[0] = (v < 0 ? '-' : v > 0 ? '+' : ' '); + + int cp = std::abs(UCI::to_cp(v)); + if (cp >= 10000) + { + buffer[1] = '0' + cp / 10000; + cp %= 10000; + buffer[2] = '0' + cp / 1000; + cp %= 1000; + buffer[3] = '0' + cp / 100; + buffer[4] = ' '; + } + else if (cp >= 1000) + { + buffer[1] = '0' + cp / 1000; + cp %= 1000; + buffer[2] = '0' + cp / 100; + cp %= 100; + buffer[3] = '.'; + buffer[4] = '0' + cp / 10; + } + else + { + buffer[1] = '0' + cp / 100; + cp %= 100; + buffer[2] = '.'; + buffer[3] = '0' + cp / 10; + cp %= 10; + buffer[4] = '0' + cp / 1; + } +} + + +// Converts a Value into pawns, always keeping two decimals +static void format_cp_aligned_dot(Value v, std::stringstream& stream) { + + const double pawns = std::abs(0.01 * UCI::to_cp(v)); + + stream << (v < 0 ? '-' + : v > 0 ? '+' + : ' ') + << std::setiosflags(std::ios::fixed) << std::setw(6) << std::setprecision(2) << pawns; +} + + +// Returns a string with the value of each piece on a board, +// and a table for (PSQT, Layers) values bucket by bucket. +std::string trace(Position& pos) { + + std::stringstream ss; + + char board[3 * 8 + 1][8 * 8 + 2]; + std::memset(board, ' ', sizeof(board)); + for (int row = 0; row < 3 * 8 + 1; ++row) + board[row][8 * 8 + 1] = '\0'; + + // A lambda to output one box of the board + auto writeSquare = [&board](File file, Rank rank, Piece pc, Value value) { + const int x = int(file) * 8; + const int y = (7 - int(rank)) * 3; + for (int i = 1; i < 8; ++i) + board[y][x + i] = board[y + 3][x + i] = '-'; + for (int i = 1; i < 3; ++i) + board[y + i][x] = board[y + i][x + 8] = '|'; + board[y][x] = board[y][x + 8] = board[y + 3][x + 8] = board[y + 3][x] = '+'; + if (pc != NO_PIECE) + board[y + 1][x + 4] = PieceToChar[pc]; + if (value != VALUE_NONE) + format_cp_compact(value, &board[y + 2][x + 2]); + }; + + // We estimate the value of each piece by doing a differential evaluation from + // the current base eval, simulating the removal of the piece from its square. + Value base = evaluate(pos); + base = pos.side_to_move() == WHITE ? base : -base; + + for (File f = FILE_A; f <= FILE_H; ++f) + for (Rank r = RANK_1; r <= RANK_8; ++r) + { + Square sq = make_square(f, r); + Piece pc = pos.piece_on(sq); + Value v = VALUE_NONE; + + if (pc != NO_PIECE && type_of(pc) != KING) + { + auto st = pos.state(); + + pos.remove_piece(sq); + st->accumulator.computed[WHITE] = false; + st->accumulator.computed[BLACK] = false; + + Value eval = evaluate(pos); + eval = pos.side_to_move() == WHITE ? eval : -eval; + v = base - eval; + + pos.put_piece(pc, sq); + st->accumulator.computed[WHITE] = false; + st->accumulator.computed[BLACK] = false; + } + + writeSquare(f, r, pc, v); + } + + ss << " NNUE derived piece values:\n"; + for (int row = 0; row < 3 * 8 + 1; ++row) + ss << board[row] << '\n'; + ss << '\n'; + + auto t = trace_evaluate(pos); + + ss << " NNUE network contributions " + << (pos.side_to_move() == WHITE ? "(White to move)" : "(Black to move)") << std::endl + << "+------------+------------+------------+------------+\n" + << "| Bucket | Material | Positional | Total |\n" + << "| | (PSQT) | (Layers) | |\n" + << "+------------+------------+------------+------------+\n"; + + for (std::size_t bucket = 0; bucket < LayerStacks; ++bucket) + { + ss << "| " << bucket << " "; + ss << " | "; + format_cp_aligned_dot(t.psqt[bucket], ss); + ss << " " + << " | "; + format_cp_aligned_dot(t.positional[bucket], ss); + ss << " " + << " | "; + format_cp_aligned_dot(t.psqt[bucket] + t.positional[bucket], ss); + ss << " " + << " |"; + if (bucket == t.correctBucket) + ss << " <-- this bucket is used"; + ss << '\n'; + } + + ss << "+------------+------------+------------+------------+\n"; + + return ss.str(); +} + + +// Load eval, from a file stream or a memory stream +bool load_eval(std::string name, std::istream& stream) { initialize(); fileName = name; return read_parameters(stream); - } +} - // Save eval, to a file stream or a memory stream - bool save_eval(std::ostream& stream) { +// Save eval, to a file stream or a memory stream +bool save_eval(std::ostream& stream) { if (fileName.empty()) - return false; + return false; return write_parameters(stream); - } +} + +// Save eval, to a file given by its name +bool save_eval(const std::optional& filename) { + + std::string actualFilename; + std::string msg; + + if (filename.has_value()) + actualFilename = filename.value(); + else + { + if (currentEvalFileName != EvalFileDefaultName) + { + msg = "Failed to export a net. " + "A non-embedded net can only be saved if the filename is specified"; + + sync_cout << msg << sync_endl; + return false; + } + actualFilename = EvalFileDefaultName; + } + + std::ofstream stream(actualFilename, std::ios_base::binary); + bool saved = save_eval(stream); + + msg = saved ? "Network saved successfully to " + actualFilename : "Failed to export a net"; + + sync_cout << msg << sync_endl; + return saved; +} + -} // namespace Stockfish::Eval::NNUE +} // namespace Stockfish::Eval::NNUE